Transforming Aspirational Districts (TAD)

In the first half of 2018, the Trusts partnered with NITI Aayog for transforming 112 districts in 27 states through convergence of central and state schemes, collaboration of central and state-level ‘Prabhari’ officers and district collectors, and a competition among districts driven by mass movement. 

The role of the Trusts is to support the collection, monitoring and evaluation of data across 85 districts in 27 states. FREND, a Section 8 company set-up by the Trusts in collaboration with Google India, is the implementation partner.

Key highlights of the programme

• Enables performance benchmarking at a district-level, and the set-up of governance across 85 of the 112 aspirational districts identified by NITI Aayog, through a digital data collection process across various sectors such as health, education, livelihood, financial inclusion and basic infrastructure.
• Ensures effective delivery of a large-scale data collection exercise through strategic coordination between community, implementation, technology, capacity-building, knowledge management, and research and development partners.
• Builds capacity in field and data enumeration teams to fulfil the requirements of the data collection exercise using mobile apps, while ensuring data quality, privacy and confidentiality.
• Derives insights from data and field observation, and streamlines district planning and processes to improve indicators.

Key achievements

• NITI Aayog released the first DELTA ranking in December 2018 based on survey results. This has prompted district administrations to relook at the data reported on the portal. This significant move certainly contributes to rationalising performance benchmarking, leading to further development of the aspirational districts.
• A post-survey District Variation Report of 85 aspirational districts was prepared and submitted to NITI Aayog. This has facilitated a discourse over data authenticity and reliability under the TAD programme.
• Over 700,000 individuals from over 4,000 villages and over 10,000 institutions from 85 districts were covered in the data which had 42 different indicators.
• A total of 205 training batches were organised during two rounds of surveys and 1,150 local field team members were also trained in two rounds.
• A customised mobile app was developed to collect data using dynamic technology and in-field randomisation for sampling.
• Content for the surveys and training sessions were adapted in 17 regional languages to cater to the regional diversity and needs of 27 states.
• A dashboard was prepared to monitor the progress of the survey on real-time basis.